| 1 |
Author(s):
Dr. Sridhar Reddy.
Page No :
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AI-Driven Early Detection of Rare Genetic Disorders in Neonates
Abstract
Early detection of rare genetic disorders in neonates is crucial for timely intervention and improved clinical outcomes. Traditional diagnostic methods face limitations including lengthy turnaround times, fragmented data, and reliance on clinician expertise, which often delay diagnosis. Artificial Intelligence (AI), through advanced machine learning and deep learning algorithms, offers a transformative approach by rapidly analyzing complex genomic, phenotypic, and clinical data to identify patterns indicative of rare diseases. Integrating AI with neonatal screening programs enhances diagnostic accuracy, reduces the diagnostic odyssey, and enables personalized care. Despite challenges such as data privacy, algorithmic bias, and ethical considerations, ongoing advancements in AI and collaborative efforts promise to revolutionize neonatal care. This article explores the role of AI in genomic and phenotypic data analysis, real-world applications, benefits, challenges, and future prospects of AI-driven early detection of rare genetic disorders in neonates.
| 2 |
Author(s):
Arun Kumar.
Page No : 1-3
|
Nanodiagnostics: Enhancing Early Detection of Infectious Diseases
Abstract
Early detection of infectious diseases is crucial for effective treatment and controlling outbreaks. Conventional diagnostic methods often suffer from limitations such as low sensitivity, long processing times, and the need for sophisticated laboratory infrastructure. Nanodiagnostics, which involves the use of nanoscale materials and devices for diagnostic purposes, is revolutionizing the field by offering highly sensitive, rapid, and cost-effective detection platforms. Nanomaterials including quantum dots, gold nanoparticles, carbon nanotubes, and magnetic nanoparticles possess unique optical, electrical, and magnetic properties that enhance biosensor performance. This paper reviews recent advances in nanodiagnostic technologies for infectious disease detection, highlighting innovations in biosensors, point-of-care devices, and multiplexed assays. It discusses challenges related to clinical translation, including reproducibility, standardization, and regulatory approval, while envisioning future directions toward integrated and personalized diagnostic systems.
| 3 |
Author(s):
Shamanth Devraj.
Page No : 1-3
|
The Integration of Nanotechnology in Point-of-Care Diagnostic Devices
Abstract
Point-of-care (POC) diagnostic devices have revolutionized healthcare by enabling rapid, accurate, and on-site detection of diseases, thereby facilitating timely clinical decisions and improved patient outcomes. The integration of nanotechnology into POC diagnostics has significantly enhanced device sensitivity, specificity, and multiplexing capabilities. Nanomaterials such as gold nanoparticles, quantum dots, carbon nanotubes, and magnetic nanoparticles provide unique optical, electrical, and magnetic properties that can be harnessed to develop miniaturized, portable, and highly efficient biosensors. This paper comprehensively reviews the advancements in nanotechnology-enabled POC devices, focusing on the design principles, nanomaterial applications, and the challenges faced in clinical translation. It highlights successful case studies including COVID-19 rapid tests, glucose sensors, and infectious disease diagnostics. Finally, it discusses future perspectives involving smart wearable diagnostics, integration with digital health platforms, and the role of artificial intelligence in enhancing POC testing.
| 4 |
Author(s):
Nithin Joshuva and Supritha shine .
Page No : 1-3
|
The Role of Human Resource Practices in Enhancing Teacher Performance and Student Outcomes
Abstract
Human Resource Management (HRM) in educational institutions has evolved from an administrative necessity to a strategic function that directly impacts the quality of education. This paper explores the influence of HRM practices—particularly recruitment, training, performance appraisal, motivation, and retention—on teacher performance and student outcomes. Through a comprehensive literature review of fifteen peer-reviewed sources, the paper demonstrates that effective HRM not only enhances teacher satisfaction and effectiveness but also significantly improves student achievement. Recommendations are provided for educational leaders to align HR strategies with pedagogical goals to foster academic excellence.
| 5 |
Author(s):
Nishant Kapoor.
Page No : 1-3
|
Artificial Intelligence in Precision Medicine: Personalizing Diagnosis and Treatment Plans
Abstract
Precision medicine represents a paradigm shift in healthcare by tailoring medical treatment to the individual characteristics of each patient, including their genetic makeup, environment, and lifestyle. Artificial Intelligence (AI) plays a pivotal role in realizing the full potential of precision medicine by analyzing vast, complex datasets to generate predictive models, identify biomarkers, and optimize treatment strategies. This paper provides a comprehensive review of AI applications in precision medicine, highlighting key technologies such as machine learning, deep learning, and natural language processing. It discusses AI-driven approaches for genomic data interpretation, patient stratification, and treatment recommendation systems. The integration of multi-omics data, electronic health records, and real-world evidence through AI enables more accurate disease diagnosis and personalized therapeutic interventions. Challenges related to data heterogeneity, interpretability, ethical considerations, and clinical adoption are examined. The paper concludes with future perspectives on AI’s transformative impact on precision medicine, emphasizing the need for collaborative frameworks, robust validation, and regulatory compliance to ensure patient safety and maximize clinical benefit.
| 6 |
Author(s):
Mamatha Gugulothu.
Page No : 1-4
|
Securing Data Endpoints in Google Cloud: A Data-Driven Approach to Anomaly Detection and Threat Mitigation
Abstract
Using Google Cloud requires a complete defensive plan combining data-based anomaly alerts with early threat response systems to protect confidential information. Modern cloud environments require active security monitoring because their complexity continues to increase while cyber threats become more complex. Traditional security practices fail to handle the fluid characteristics of cloud-based data breaches because organizations must move towards security systems based on data intelligence. The research presents an analysis of advanced anomaly detection methods through statistical analysis, machine learning algorithms, and behavior analytics for observing and responding to abnormal data access patterns and security incidents in Google Cloud infrastructures. Organizations that deploy robust anomaly detection systems create better capabilities for threat detection, along with threat mitigation, and ensure compliance with strict regulatory requirements. Companies require integrated security platforms because cyber dangers combine with financial problems and system breakdowns within a single detection foundation.
| 7 |
Author(s):
Dev Kukreja.
Page No : 1-4
|
A Study on Welfare of Employees for Job Satisfaction
Abstract
Employee weal plays a vital part in promoting job satisfaction and enhancing organizational productivity. This exploration explores the relationship between hand weal schemes and job satisfaction within an organizational environment. The study aims to identify crucial weal measures and assess their effectiveness through primary data collection and analysis
| 8 |
Author(s):
RUPAL SHARMA .
Page No : 1-4
|
Time Management and Its Effect in Reducing Stress among Students
Abstract
Effective time administration may be a basic expertise for understudies pointing to adjust scholarly duties, extracurricular exercises, and individual life. This ponder investigates the relationship between time administration hones and stretch lessening among understudies. It looks at how setting needs, arranging errands, and dodging lingering can altogether impact students' mental well-being and scholastic execution. Information was collected through studies and interviews from a test of tall school and college understudies. The discoveries demonstrate that understudies who utilize viable time administration methodologies involvement lower levels of stretch and higher levels of scholarly fulfillment. The think about concludes that advancing time administration instruction can be a important apparatus in decreasing push and improving understudy success.
| 9 |
Author(s):
Pavan T.K.
Page No : 1-4
|
Fungal and Bacterial Nanofactories: A Green Technology Approach to Ecosystem Management
Abstract
The rise of nanotechnology has paved the way for innovative environmental management strategies, among which microbial nanofactories—especially those harnessing fungi and bacteria—stand out as eco-friendly, cost-effective, and sustainable approaches. These living nanofactories synthesize nanoparticles with unique physicochemical properties under ambient conditions, bypassing the need for harsh chemicals or energy-intensive methods. The biologically produced nanoparticles have diverse applications, including pollutant degradation, soil and water remediation, pathogen control, and nutrient cycling enhancement. This review explores the mechanisms underlying fungal and bacterial nanoparticle synthesis, their environmental applications, and contributions to ecosystem management. We critically assess the advantages of microbial nanofactories as green nanotechnologies, discuss challenges related to scale-up and ecological safety, and outline future perspectives for integrating these biogenic nanomaterials into sustainable ecosystem management frameworks.
| 10 |
Author(s):
Aakifa Maryam.
Page No : 1-4
|
Ecological Risks and Remediation Potential of Bio-Nano Hybrids
Abstract
Bio-nano hybrids, which integrate biological components with engineered nanomaterials, have gained considerable attention for their potential in environmental remediation. These hybrid systems harness the unique physicochemical properties of nanoparticles alongside the biological specificity and adaptability of microorganisms, enzymes, or biomolecules, thus enhancing pollutant degradation, sequestration, and detoxification processes. Their applications span wastewater treatment, soil remediation, and pathogen control, offering a sustainable alternative to conventional chemical treatments. However, despite these promising applications, bio-nano hybrids pose complex ecological risks due to their multifaceted interactions with natural ecosystems. The dual nature of these materials necessitates comprehensive understanding of their environmental fate, toxicity mechanisms, and long-term impacts. This review critically evaluates the remediation capabilities of bio-nano hybrids and examines their ecological risks, highlighting recent advances, knowledge gaps, and future perspectives. Emphasis is placed on safe-by-design approaches, regulatory challenges, and the imperative for interdisciplinary research to optimize benefits while minimizing unintended consequences.
| 11 |
Author(s):
Nithin Kumar.
Page No : 1-4
|
Soil-Root-Microbe-Nano Interactions: Toward Sustainable Plant-Microbiome Systems
Abstract
The intricate interactions among soil, plant roots, microbial communities, and nanomaterials are at the forefront of research in sustainable agriculture and environmental health. As global agricultural systems face pressures from climate change, soil degradation, and chemical overuse, integrating nanotechnology with plant-microbiome science emerges as a promising strategy for building resilient and productive ecosystems. This review explores the multifaceted relationships within soil-root-microbe-nano systems, highlighting how nanomaterials can influence microbial dynamics, nutrient availability, root architecture, and plant health. The role of engineered and biosynthesized nanoparticles in shaping rhizosphere microbiomes, enhancing nutrient use efficiency, and suppressing pathogens is examined. Further, the feedback mechanisms between nanomaterials and microbial metabolites, soil physicochemical properties, and root exudates are discussed in the context of ecological stability. While the synergistic applications of nanotechnology and microbiology in plant systems present substantial opportunities, this article also addresses the ecological risks and biosafety concerns associated with nanoparticle deployment. A transdisciplinary approach that considers soil health, microbial ecology, nanotoxicology, and sustainable agricultural practices is essential for developing functional plant-microbiome systems for the future.
| 12 |
Author(s):
Amarnath Desai.
Page No : 1-4
|
Microbial Engineering and Nanotechnology: Tools for Restoring Ecological Integrity
Abstract
Restoring ecological integrity has become a global imperative in the face of accelerated environmental degradation, biodiversity loss, and anthropogenic pollution. Microbial engineering and nanotechnology, two powerful and rapidly advancing fields, offer innovative strategies to rehabilitate ecosystems and promote environmental sustainability. This review explores how genetically engineered microorganisms (GEMs), synthetic microbial consortia, and nanomaterials—both engineered and biogenic—are being harnessed to remediate contaminated environments, improve soil and water quality, and support resilient ecosystems. It also discusses the synergistic potential of combining microbial engineering with nanotechnological interventions to enhance pollutant degradation, metal recovery, nutrient cycling, and biotic stress management. Emphasis is placed on the ecological applications of microbe-nano hybrids, biocompatible nanomaterials, and engineered biosensors. While these technologies offer promising routes to environmental restoration, the article also addresses biosafety concerns, ecological risks, and ethical considerations associated with deploying engineered systems in natural habitats. A systems-level, interdisciplinary approach is advocated to responsibly and effectively implement microbial-nano solutions for restoring ecological balance and resilience.
| 13 |
Author(s):
Simran. I.
Page No : 1-4
|
Integrative Approaches Using Microbes and Nanomaterials in Urban Environmental Health
Abstract
The rapid urbanization witnessed globally has intensified environmental challenges such as air and water pollution, waste accumulation, and deteriorating public health. Traditional mitigation strategies often fall short in terms of sustainability and efficiency. Recent scientific advancements propose a synergistic approach involving microbes and nanomaterials to address these issues in urban settings. This review explores the integrative potential of microbial biotechnology and nanoscience to manage urban environmental health challenges. Microbes offer ecological services such as biodegradation, pollutant detoxification, and biosorption, while nanomaterials enhance these capabilities through improved delivery, reactivity, and sensing. The convergence of these two technologies facilitates the development of innovative solutions, including microbial-nanocomposites for bioremediation, nano-enabled biosensors for real-time environmental monitoring, and microbial platforms for nanomaterial synthesis. This review presents current research trends, applications, and challenges in deploying these integrated technologies to promote urban environmental sustainability and public health resilience.
| 14 |
Author(s):
Koushik Raj.
Page No : 1-4
|
Nanotechnology in the Development of Antimicrobial Agents
Abstract
The emergence of multidrug-resistant pathogens poses a severe global health challenge, threatening the efficacy of conventional antibiotics and demanding innovative strategies to combat infectious diseases. Nanotechnology offers promising avenues for developing novel antimicrobial agents that overcome resistance mechanisms, enhance drug delivery, and reduce toxicity. By exploiting unique physicochemical properties at the nanoscale, nanomaterials can exhibit intrinsic antimicrobial activity or serve as carriers for controlled release of existing drugs. This paper provides an extensive review of recent advances in nanotechnology-enabled antimicrobial agents, highlighting various nanomaterials such as metallic nanoparticles, polymeric nanocarriers, and lipid-based systems. It examines the mechanisms through which nanomaterials exert antimicrobial effects, their applications against bacteria, fungi, and viruses, and the challenges related to toxicity and clinical translation. Furthermore, the paper discusses future perspectives including multifunctional nanocomposites and synergistic approaches that can potentially revolutionize antimicrobial therapy and address the urgent problem of antibiotic resistance.
| 15 |
Author(s):
Satish Naik.
Page No : 1-4
|
Safety and Toxicological Assessments of Biomedical Nanomaterials
Abstract
Biomedical nanomaterials have ushered in a new era in healthcare by enabling revolutionary advancements in drug delivery, diagnostic imaging, regenerative medicine, and biosensing. These materials possess unique physicochemical properties such as nanoscale size, high surface area-to-volume ratios, and surface functionalization, which allow for improved therapeutic targeting and efficacy. However, these same properties raise critical concerns about their interactions with biological systems and potential adverse health effects. This paper provides a comprehensive review of the current landscape of safety and toxicological assessments of biomedical nanomaterials. It examines the underlying mechanisms of nanotoxicity, evaluates in vitro, in vivo, and computational testing methods, and explores regulatory frameworks designed to ensure safety. Furthermore, it highlights ongoing challenges such as variability in nanomaterial characterization, data gaps in long-term toxicity, and lack of standardized protocols. The paper concludes by discussing future perspectives to advance nanotoxicology research, emphasizing interdisciplinary collaboration, standardization, and the integration of novel technologies to support the safe clinical translation of nanomedicine.
| 16 |
Author(s):
Manoj Shetty.
Page No : 1-4
|
Nanocarriers for Gene Therapy: Progress and Challenges
Abstract
Gene therapy has emerged as a revolutionary approach in modern medicine, aiming to treat, prevent, or even cure a wide range of genetic, acquired, and infectious diseases by introducing therapeutic nucleic acids into patient cells. Despite its potential, one of the foremost challenges remains the effective and safe delivery of these genetic materials, which are inherently unstable and susceptible to degradation in biological environments. Nanocarriers—engineered nanoscale delivery vehicles—have been increasingly recognized as promising platforms for gene delivery because of their ability to encapsulate, protect, and transport nucleic acids efficiently to targeted cells or tissues while minimizing off-target effects and toxicity. This paper provides an in-depth review of the various types of nanocarriers currently utilized in gene therapy, including lipid-based nanoparticles, polymeric carriers, inorganic nanoparticles, and hybrid systems. It also explores key technological advances in nanocarrier design that enhance delivery efficiency, cellular uptake, and endosomal escape. Additionally, clinical applications and ongoing trials illustrate the translational progress of nanocarrier-mediated gene therapies. Challenges such as immunogenicity, off-target effects, large-scale production, and regulatory hurdles are critically analyzed. Finally, future perspectives focusing on personalized nanocarriers, multifunctional platforms, and AI-driven optimization are discussed, emphasizing their potential to transform gene therapy into a mainstream therapeutic modality.
| 17 |
Author(s):
SHIVAM JAWLA, Rohan Patel, Santosh Patel, Sadhana Dubey.
Page No : 1-4
|
Optimizing Multicloud Data Lakes with Delta Lake and Unity Catalog for Regulated Industries
Abstract
The transition of highly regulated industries towards a multicloud approach for enhanced resilience, scalability, and vendor-neutral data architectures highlights the critical importance of implementing a unified, compliant, and high-performance data fabric. This paper explores Delta Lake and Unity Catalog on Databricks as methods for creating scalable, secure, and compliance-ready data lakes on AWS and Azure. We examine architectural forms, governance systems, and performance enhancement strategies suitable for finance, healthcare, and governmental entities.
| 18 |
Author(s):
Dr. Megha Jain.
Page No : 1-4
|
The Influence of Demographic Factors and User Interface on Internet Banking Adoption: An Empirical study
Abstract
Information technology has played a crucial role in the financial services. Internet has proved a magic wand for financial services and products, banking in particular. Banking sector has been early adopter of technology to offer latest modes for transacting business. Banks have transformed themselves and are offering services through internet. From computerization to networking to ATMs and now E-Banking, banks have moved up the value chain this transformal change have been dealt with in this study. The main focus has been on exploring the impact of Demographical variables on Internet banking adoption. Due importance also has been accorded to the overall customer satisfaction towards Internet banking services.
| 19 |
Author(s):
B. Tanuja, CH. Varsha, G. Eshwar, K. Rohith, Mr. K. Vijay.
Page No : 1-4
|
AUTOMATED IMAGE CAPTIONING GENERATOR USING DEEP LEARNING
Abstract
The increasing volume of visual data shared online highlights the need for systems that can understand and describe images automatically. This project presents an automated image captioning generator based on deep learning techniques. The model combines Convolutional Neural Networks (CNNs) for extracting image features with Long Short-Term Memory (LSTM) networks for generating descriptive captions. Trained on a dataset of images paired with human-written captions, the system learns to produce contextually relevant and grammatically correct descriptions. This approach has broad applications in accessibility, digital content management, and image retrieval, bridging the gap between visual understanding and natural language.
| 20 |
Author(s):
Dr Manish Singh.
Page No : 1-4
|
Impact of AI in Personalizing Digital Marketing Campaigns
Abstract
In the zip-paced world of marketing, one of the most transformative advancements of late has been the integration of artificial intelligence (AI) to enhance personalization strategies. AI-powered personalization in marketing represents a sea change in how brands engage with their audiences, offering tailored experiences that not only captivate consumers, but also drive conversion rates and brand loyalty. In this post, we’re going to take a look at the dynamic landscape of AI-powered personalization in marketing and consider the key components, benefits, challenges and the future of this radical, but promising, approach.
Artificial Intelligence (AI) in digital marketing has evolved from a fantastical notion to a game-changer for today's marketers. It's become a powerful technology to drive personalization, predictive analytics, customer experiences, and much more. In today's digital age, where consumers crave personalized experiences, AI has emerged as a game-changer. Gone are the days of generic marketing campaigns. AI-powered tools analyze vast amounts of customer data to deliver tailored content, products, and services that resonate deeply.
AI is changing the game when it comes to personalized marketing. Think about how Netflix always seems to know what you’ll binge next. That's AI analyzing your watch history and suggesting content you’ll probably enjoy. Amazon does something similar, predicting what you might want to buy based on your browsing and purchase patterns. Then there’s Sephora’s chatbot, which offers beauty product recommendations in real time, almost like chatting with a helpful store assistant. Spotify’s ‘Discover Weekly’ playlist is another great example; it curates songs based on your listening habits, giving you fresh music that matches your taste. Even email platforms like Mailchimp use AI to figure out the best time to send messages and what content will grab your attention.
| 21 |
Author(s):
M.uday kumar.
Page No : 1-4
|
AI-Powered Automated System for Skin Disease Detection and Classification
Abstract
Skin cancer has become the most commonly diagnosed cancer worldwide since the 1970s, with both melanoma and non-melanoma cases increasing steadily, particularly in Western countries. According to the World Health Organization, melanoma accounts for one-third of all cancer diagnoses. In the United States, one in five individuals is expected to develop skin cancer during their lifetime. Early diagnosis significantly improves the survival rate, yet differentiating between malignant and benign lesions remains a major clinical challenge. Conventional diagnostic methods often fall short due to the visual similarity of lesions and limited access to expert dermatologists. This study investigates the use of deep learning techniques, particularly Dense Convolutional Neural Networks (DenseNet), to classify skin lesions accurately. Traditional machine learning models such as K-Nearest Neighbors, Support Vector Machines, and Decision Trees yielded suboptimal results in terms of accuracy. By contrast, our DenseNet model achieved an accuracy exceeding 86.6%, highlighting its potential for automated and precise skin cancer detection. This approach can play a vital role in aiding early diagnosis and improving patient outcomes.
| 22 |
Author(s):
Aditya Narayan.
Page No : 1-4
|
From Structured to Unstructured: A Review on NLP Applications Transforming Healthcare Data
Abstract
Healthcare data is produced at an unprecedented scale worldwide, consisting of both structured and unstructured components. Structured data such as lab values, vital signs, and diagnostic codes are traditionally easier to analyze, but they represent only a fraction of the total healthcare information. A vast majority of clinical data exists in unstructured formats, including free-text clinical notes, imaging reports, pathology narratives, and patient communications, which contain rich contextual and nuanced information. Natural Language Processing (NLP) has emerged as a critical technology for unlocking this underutilized resource by converting unstructured text into structured, computable data. This paper reviews the state-of-the-art NLP methodologies applied in healthcare, highlighting their role in transforming unstructured data into actionable knowledge. It explores key NLP techniques such as named entity recognition, relation extraction, sentiment analysis, and deep learning frameworks. The paper discusses diverse applications ranging from clinical documentation improvement and decision support to research and population health management. Challenges related to linguistic variability, domain adaptation, data privacy, and system integration are analyzed. Future prospects include real-time NLP, multilingual capabilities, and explainability, which promise to accelerate the integration of NLP-driven insights into clinical practice and research, ultimately enhancing patient care quality and operational efficiency.
| 23 |
Author(s):
Divya Sen.
Page No : 1-4
|
Bridging the AI Adoption Gap in Healthcare: Implementation Frameworks and Case Studies
Abstract
Artificial Intelligence (AI) has emerged as a transformative technology in healthcare, offering capabilities ranging from enhanced diagnostics and personalized treatment plans to optimized operational workflows. Despite its potential, the widespread adoption of AI in healthcare settings remains limited and uneven. This paper investigates the multifaceted causes of the AI adoption gap in healthcare, emphasizing the complex interplay of technological, organizational, ethical, and regulatory barriers that impede full-scale implementation. It reviews comprehensive implementation frameworks that guide healthcare institutions through the adoption process, focusing on strategies for stakeholder engagement, workflow integration, data governance, and ethical compliance. Through detailed analysis of real-world case studies, the paper illustrates successful deployment approaches, highlighting lessons learned and best practices. The findings aim to provide healthcare leaders, clinicians, and policymakers with actionable insights to bridge the gap between AI innovation and its practical application, ultimately fostering improved patient outcomes and healthcare efficiency.
| 24 |
Author(s):
Priya Tamhane.
Page No : 1-4
|
Ethical and Legal Implications of AI in Healthcare: A Global Perspective
Abstract
Artificial Intelligence (AI) technologies are increasingly embedded within healthcare systems worldwide, offering promising advances in diagnosis, treatment, and operational efficiency. However, the rapid integration of AI raises complex ethical and legal questions that vary across global regions due to differing regulatory landscapes, cultural values, and healthcare infrastructures. This paper provides a thorough examination of the ethical dilemmas and legal challenges associated with AI deployment in healthcare from a global standpoint. It explores issues such as patient privacy, algorithmic transparency, bias and fairness, liability, and informed consent. By reviewing international regulatory frameworks and guidelines, the paper highlights the diversity of approaches to AI governance and the implications for cross-border healthcare applications. Through comparative analysis and case studies, the paper underscores the necessity for harmonized policies, interdisciplinary collaboration, and proactive ethical oversight to ensure that AI adoption in healthcare is both responsible and equitable on a global scale.
| 25 |
Author(s):
Irfan Pasha.
Page No : 1-4
|
AI in Pediatric and Geriatric Healthcare: A Comparative Review of Innovations and Gaps
Abstract
Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic precision, optimizing clinical workflows, and supporting personalized care. However, its application across diverse age groups—particularly pediatric and geriatric populations—presents unique challenges and opportunities. This paper provides a comprehensive review of AI innovations in pediatric and geriatric healthcare, highlighting similarities, contrasts, and critical gaps that need to be addressed. It explores the distinctive clinical, ethical, and technical considerations in these populations, evaluates current AI-driven solutions, and discusses emerging trends in machine learning, deep learning, and natural language processing. The paper also identifies key areas where AI integration is limited, examining barriers to adoption, regulatory hurdles, and disparities in data representation. Concluding with strategic recommendations, this paper aims to inform stakeholders about the development and deployment of equitable, effective, and patient-centered AI tools that cater to the unique needs of both pediatric and geriatric patients.
| 26 |
Author(s):
Mukund Desai.
Page No : 1-4
|
Smart Diagnostic Tools: Evaluating AI-Driven Systems for Enhanced Diagnostic Accuracy
Abstract
The integration of Artificial Intelligence (AI) into diagnostic tools has emerged as a transformative force in modern healthcare. AI-driven diagnostic systems offer the potential to improve accuracy, reduce diagnostic errors, and enhance clinical efficiency. This paper provides a comprehensive evaluation of smart diagnostic tools powered by AI, exploring their capabilities, limitations, and impact on healthcare outcomes. It delves into key technological advancements, including machine learning, deep learning, and natural language processing, that underpin these systems. The paper also examines real-world applications across various medical specialties, highlighting successes, challenges, and areas where AI has reshaped clinical diagnostics. Furthermore, it addresses critical considerations such as algorithmic bias, data quality, regulatory frameworks, and integration into clinical workflows. Concluding with recommendations for future research and implementation strategies, this paper aims to inform stakeholders about the responsible deployment of AI-driven diagnostic tools to achieve enhanced diagnostic accuracy in patient care.
| 27 |
Author(s):
Charulatha Nair.
Page No : 1-4
|
AI in Healthcare Training: A Systematic Review of Tools Enhancing Surgical Competence
Abstract
The integration of Artificial Intelligence (AI) into surgical training has revolutionized the way healthcare professionals acquire, refine, and maintain competence in complex surgical procedures. AI-powered tools such as virtual reality simulators, intelligent tutoring systems, and performance analytics platforms have significantly enhanced the quality and efficiency of surgical education. This paper presents a systematic review of AI-driven tools designed to enhance surgical competence, examining their technological underpinnings, applications, and impact on clinical training. It also highlights the benefits and limitations of AI integration in surgical education, discusses regulatory and ethical considerations, and offers recommendations for future development and implementation. By providing a comprehensive analysis of current evidence and best practices, this paper aims to inform educators, policymakers, and clinicians about the transformative role of AI in surgical training and its potential to improve patient outcomes through enhanced surgical proficiency.
| 28 |
Author(s):
Manjula Naik.
Page No : 1-4
|
The Role of Machine Learning in Predicting Healthcare Outcomes: A Patient-Centric Approach
Abstract
Machine learning (ML) has emerged as a transformative force in healthcare, enabling more accurate and timely prediction of patient outcomes by analyzing complex and heterogeneous datasets. By leveraging diverse data sources, ML algorithms uncover subtle patterns and risk factors often missed by traditional statistical methods. This paper comprehensively explores the pivotal role of machine learning in healthcare outcome prediction, emphasizing a patient-centric approach that integrates individual patient characteristics and preferences to tailor care effectively. The discussion spans the variety of ML techniques employed, the types of clinical and non-clinical data utilized, and specific applications across medical specialties that enhance clinical decision-making and enable proactive interventions. It also critically addresses challenges such as data privacy, model transparency, bias, and integration hurdles in clinical workflows. Finally, the paper outlines future directions where advancements in explainable AI, federated learning, and patient engagement can further refine predictive models to improve healthcare delivery and outcomes.
| 29 |
Author(s):
Rajesh Naik .
Page No : 1-4
|
Enhancing IOT Data Security in Wireless Sensor Networks Using Blockchain Technology
Abstract
-The rapid growth of Internet of Things (IoT) devices within wireless sensor networks (WSNs) is reshaping various sectors, including smart cities, healthcare, and environmental monitoring. While these advancements bring new opportunities, they also raise serious security concerns— particularly around data integrity, privacy, and access control. Conventional security methods often struggle to keep up due to the decentralized and resource-limited nature of WSNs. This paper investigates how blockchain technology can be used to strengthen the security of IoT data in these networks. By taking advantage of blockchain’s core features— decentralization, transparency, and immutability—we introduce a framework that enhances secure data transmission, user authentication, and accountability. Our approach helps protect against common threats like data tampering, spoofing, and unauthorized access. In addition to outlining the technical design, we examine both the benefits and the practical challenges of implementing blockchain in real-world WSN environments. The goal is to assess whether blockchain can offer a scalable and reliable security solution for the evolving IoT landscape. Ultimately, our findings suggest that blockchain holds strong potential to reinforce trust, ensure data protection, and support the safe expansion of IoT applications
| 30 |
Author(s):
Shreyas B V, Dr.Sridhara S.
Page No : 1-4
|
Feasibility Studies on an Eco-friendly Water Purification Unit using Polystyrene Beads
Abstract
Water is the basis of all life. But, the quality of drinking water has been deteriorated due to various anthropogenic activities. There is a need for an efficient and eco-friendly water treatment method as the conventional methods are inconsistent and release excess of waste water. Polystyrene, a synthetic resin can be used as a packed media filter to purify water by ion-exchange method. The ion-exchange process using synthetic resin is the most effective method for the removal of selective ions from water. This method is widely used for the removal of nitrates, fluorides, iron and hardness of water. Treatability studies will be conducted by filling the column with polystyrene beads as a packed media. In this research water quality assessment of both the sample water and the purified water will be done on a daily basis to check if the water quality standards will be achieved. Also, Media exhaustion studies will be conducted which determines the durability of the filter material for effective purification of water. Along with the life span of the material, observations will be made for degradation of filter material and release of any by-products such as styrene into purified water in the long run. Based on the results, Polystyrene beads will be used to develop a home-based water purification unit.
| 31 |
Author(s):
Avijit Shukla.
Page No : 1-5
|
The Impact of Witnessing Spousal Sexual Violence on Children and Juvenile Sexual Delinquency
Abstract
Over 40 million children under the age of 18 live in India. According to a WHO report, one in three women have been the victim of sexual or physical abuse at some point in their lives. Domestic violence is an unavoidable reality. According to the National Family Health Survey (NFHS), 2019–2021, 3.1 percent of pregnant Indian women between the ages of 18 and 49 experienced physical violence during their pregnancy, and 29.3 percent of married Indian women between the ages of 18 and 49 have experienced domestic or sexual violence. The world is aware of these reported lodged figures. The irony is that the majority of these cases in our nation go unreported. The future of this country, or "the children," is the answer to the question of who is most impacted by these acts. When children see their parents acting violently, it has a profound effect on their mental health. This essay looks at the effects of seeing such behavior at home and how it relates to sexual and juvenile delinquency.
Key Words: Juvenile Delinquency, Sexual Delinquency, Domestic Violence, Children, Spousal Violence
| 32 |
Author(s):
Deepak Shende.
Page No : 1-5
|
ANALYSIS AND DETECTION OF AUTISM SPECTRUM DISORDER BY USING MACHINE LEARNING TECHNIQUES
Abstract
Autism Spectrum Disorder (ASD) is a developmental condition that affects communication and social interaction, typically emerging in early childhood. This study investigates the use of machine learning algorithms—including Naïve Bayes, Support Vector Machine, Logistic Regression, K-Nearest Neighbors, Neural Networks, and Convolutional Neural Networks (CNN)—to predict ASD in children, adolescents, and adults. Three publicly available ASD screening datasets were used, containing 292 (children), 704 (adults), and 104 (adolescents) instances respectively. After handling missing values and preprocessing, CNN outperformed all other models, achieving prediction accuracies of 99.53% for adults, 98.30% for children, and 96.88% for adolescents, indicating its high effectiveness.
KeyWords: Autism Spectrum Disorder (ASD), Machine Learning, Convolutional Neural Network (CNN), Classification, Naïve Bayes, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbors (KNN), Neural Networks, ASD Screening, Predictive Modeling.
| 33 |
Author(s):
Khushi Singh, Kawalpreet Sharma .
Page No : 1-5
|
Effects of generative AI on brand digital content production and storytelling.
Abstract
The arrival of generative AI has revolutionized digital media production and narrative for certain brands. This paper discovers how AI technologies such as GPT-based text generators, AI image and video generators, and automated content platforms are revolutionizing existing marketing practices. While AI achieves maximum efficiency, scalability, and data-driven storytelling, authenticity, originality, and ethics rule. This research explores how the role of generative AI is changing to influence brand storytelling, the challenge to human creativity and emotional connection, and the future path for content creation with collaboration between AI and humans. Through case studies and business applications and previous growth, this paper sets out how brands can attain benefits from AI without compromising and consumer trust. The report states that although generative AI is a strong force, human control is required to ensure that stories are worth reading, ethical, and effective.
| 34 |
Author(s):
G. Hemalatha, CH Jayanth, B. Sai. Sushanth, K. Achyuth, Ms. Priyanka.
Page No : 1-5
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COMPUTATIONAL MINING OF NUTRITIONAL COMPONENT FOR NON- COMMUNICABLE DISESAE ANALYSIS
Abstract
Suitable nutritional diets have been widely recognized as important measures to prevent and control non-communicable diseases (NCDs). However, there is little research on nutritional ingredients in food now, which are beneficial to the rehabilitation of NCDs. The rising global prevalence of Non-Communicable Diseases (NCDs) such as diabetes, cardiovascular diseases, and obesity highlights the urgent need for accessible preventive healthcare tools. This project presents an interactive web-based application designed to analyse user’s dietary habits and assess their potential risk for developing NCDs based on nutritional intake. The system allows users to select consumed food items, input quantities, and receive a detailed nutrient breakdown. By comparing these values against recommended thresholds, the application identifies potential NCD risks and presents results through intuitive visualizations, including graphs, for easy interpretation. A key feature of this platform is its AI-powered chatbot, which provides real-time nutritional guidance and answers user queries about food and health. Additionally, an educational module offers comprehensive information on common NCDs including causes, symptoms, and dietary recommendations promoting awareness and healthier lifestyle choices.
| 35 |
Author(s):
Afreen Mehek.
Page No : 1-5
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The Evolution of AI in Rehabilitation: Enhancing Recovery with Intelligent Systems
Abstract
Artificial Intelligence (AI) has profoundly influenced the field of rehabilitation medicine by introducing intelligent systems that significantly enhance patient recovery processes. This paper explores the historical evolution, current state, and future potential of AI applications in rehabilitation. It details how AI-driven technologies optimize personalized treatment plans, monitor patient progress, and facilitate adaptive therapies. The review encompasses a range of AI tools such as robotic-assisted therapy, virtual reality (VR) and augmented reality (AR) rehabilitation, wearable sensors, and advanced machine learning algorithms that collectively improve the effectiveness, precision, and efficiency of rehabilitation care. The challenges of integrating AI—including data integration, patient engagement, regulatory compliance, and ethical considerations—are thoroughly discussed. Furthermore, the paper presents case studies showcasing successful real-world AI implementations in rehabilitation and examines future directions emphasizing more sophisticated, patient-centered intelligent systems that promise to revolutionize the landscape of rehabilitation and healthcare delivery.
| 36 |
Author(s):
Mahantesh Shikari.
Page No : 1-5
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Clinical Data Mining with AI: Unlocking Insights from EHRs and Medical Narratives
Abstract
The rapid expansion of electronic health records (EHRs) and medical narratives has transformed healthcare into a data-rich domain. Yet, extracting meaningful insights from these vast repositories remains a complex challenge. Artificial Intelligence (AI)-driven clinical data mining emerges as a powerful tool to uncover hidden patterns, enhance diagnostic precision, and optimize patient outcomes. This paper presents an in-depth exploration of AI techniques used in clinical data mining, focusing on structured EHR data and unstructured medical narratives. It discusses foundational concepts, key methodologies, real-world applications, challenges, and future directions. Case studies illustrate how AI systems have improved early disease detection, personalized treatments, pharmacovigilance, and healthcare resource management. The paper concludes by emphasizing the need for ethical frameworks, interpretability, and continuous innovation to fully harness the transformative potential of AI in clinical data mining.
| 37 |
Author(s):
Ramya Vani Rayala, Sireesha Kolla.
Page No : 1-5
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Proactive Cyber Defense: AI in Supply Chain Risk Management
Abstract
Proactive cyber defense, particularly through the integration of AI in supply chain risk management, represents a critical evolution in cybersecurity strategies. By leveraging artificial intelligence, organizations can anticipate and mitigate potential threats across their supply chains with greater precision and speed. AI algorithms analyze vast amounts of data in real time, identifying anomalies, assessing vulnerabilities, and predicting emerging risks before they manifest into significant security breaches. This proactive approach not only enhances overall resilience but also allows for preemptive measures to secure critical assets and maintain operational continuity. As businesses increasingly rely on interconnected supply networks, the application of AI in supply chain risk management becomes indispensable in safeguarding against evolving cyber threats and ensuring sustained business resilience.
| 38 |
Author(s):
Dr. Palak Keshwani.
Page No : 1-5
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A Comprehensive Comparative Study of Routing Protocols in Wireless Sensor Networks
Abstract
Wireless Sensor Networks (WSNs) have emerged as a transformative technology with extensive applications across various domains, including environmental monitoring, healthcare, smart cities, and industrial automation. These networks consist of a multitude of small sensor nodes that collaborate to collect, process, and transmit data wirelessly. Efficient routing of data packets within WSNs is essential for ensuring reliable communication while conserving energy resources. In this paper, we conduct a comprehensive comparative study of different routing protocols used in WSNs. By analyzing the advantages, disadvantages, and applications of these protocols, we aim to provide valuable insights for researchers and practitioners seeking to optimize the performance of WSNs in diverse scenarios.
| 39 |
Author(s):
Krzysztof Rajczykowski, Andrzej Matuszowicz, Ryszard Kurowski.
Page No : 1-5
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Influence of the modification method on the immobilization ratio of crown ethers on the chitosan resin
Abstract
In the presented study, a chitosan resin was modified by hydroxydibenzo-14-crown-4 ether, which is a highly selective complexing agent, often used in lithium extraction processes. Three immobilization methods of the analysed ether were investigated: surface modification of dry chitosan beds, modification of fresh, wet resin, and pre-polymerization modification in solution. The immobilization efficiency was evaluated by analysing organic residues in post-modification and storage solutions, while structural and morphological changes were assessed using SEM imaging. The pre-polymerization method resulted in the highest immobilization efficiency (over 90%), likely due to the incorporation of the crown ether into the resin matrix. The second highest immobilization ratio was observed for a fresh resin modification, obtaining over 30% immobilization of crown ether on the surface of chitosan beds. One of the possible explanations for these results is that the hydration state significantly affects reagent diffusion and surface coverage. SEM analysis revealed that each method induced distinct microstructural transformations, with pre-polymerization modification, giving the most porous and irregular surface morphology. These results demonstrate that the modification technique critically influences both the functional and structural properties of the chitosan resin, which may impact its future applications in different kinds of metal recovery processes.
| 40 |
Author(s):
Ranjita Gandhi.
Page No : 1-5
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Role of Jharcraft’ in Transforming The Rural women Talent and Women Empowerment
Abstract
Empowerment of women is a major social phenomenon which requires an understanding of its multi-dimensional influence, including our family structures. Women must be economically and socially empowered through focused efforts. Women's concerns have to be kept at the centre of public policy, developmental planning and governance, with recognition of their role as critical growth agents and as ambassadors of social change. Major attributes that contribute to women empowerment are education, social equity and status, improved health, economic or financial stability and political participation. It is important to realize that there is significant variation in the degree of socio- economic development among Indian states. Hence it is not feasible to develop a single model for empowering Indian women as a single blueprint of state policies. Women have the power to give a life and 'Jharcraft' a strong backbone of the Jharkhand state, believes that she is naturally empowered to change lives as well as play important roles in family. She forms a better half of the society. The golden history of the nation points to the fact that the future of the nation can't be directed towards glory without women participation. Women employment is a matter of major concern of the organization so as to make them self dependent. Jharcraft enables women to look after their family well, educates their family and society. This paper explores the avenues available for the rural women talent in Jharkhand through Jharcraft for promoting women empowerment. Jharcraft was established in 2006 to develop, support and manage rural talent, sericulture farmers, weavers and artisans. With the mission of creating opportunities and changing lives, Jharcraft aims to strengthen the rural cottage industry and providing market access to the artisans and weavers in the rural areas. It aims also to support nature by preserving the natural wealth. Jharcraft opens up new opportunities of employment by utilization of the available resources, The organization pays major attention that the local artisans and unprivileged section of the state get maximum benefit through Jharcraft. Through Jharcraft each woman earns around Rs. 4000/- to Rs. 5000/- per month which enables them to look well after their family, educate their children, and contribute to the betterment of the family and society. Through maximum utilization of natural resources and labour power available in the rural areas of the state, Jharcraft aims to provide each hand its value and add to employment and income generation.
| 41 |
Author(s):
Dr Varun Bal.
Page No : 1-6
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Artificial Intelligence in the 2020s: Key Trends, Innovations, and Future Directions
Abstract
Artificial Intelligence (AI) has emerged as a transformative force across multiple sectors, redefining business operations, social interactions, and policy frameworks. This study explores recent trends in AI development and deployment, with a specific focus on advancements between 2020 and 2025. Drawing on academic literature, industry reports, and global policy developments, the paper highlights the rise of generative AI, increasing investments, sector-specific applications, and growing concerns around ethics and governance. Using a systematic literature review methodology, it identifies six dominant themes: the proliferation of generative models, ethical and regulatory challenges, labor market impacts, geopolitical dynamics, and sectoral integration. The paper concludes that while AI presents substantial opportunities for innovation and economic growth, it also necessitates robust policy mechanisms and responsible integration strategies to address emerging risks. The findings provide valuable insights for researchers, practitioners, and policymakers navigating the complex AI landscape in India and globally.
| 42 |
Author(s):
YASH PATEL.
Page No : 1-6
|
A Study on Customer Satisfaction Towards ZUDIO, Pandri Raipur c.g.
Abstract
Customer satisfaction is a crucial metric for business success, especially in retail fashion. This study evaluates customer satisfaction at ZUDIO, Pandri Raipur, focusing on product variety, quality, physical evidence, and overall store experience. Using primary data from 50 customers, the research identifies satisfaction levels and areas for improvement.
| 43 |
Author(s):
Kawalpreet Sharma, Khushi Singh .
Page No : 1-6
|
Lifestyle Challenges: The Impact of Eating Habits and Disorders on Individuals and Society
Abstract
ABSTRACT
In our modern society, the prevalence of marketing and marketing messages has created a culture of excessive consumption and has resulted in individuals becoming compulsive eaters due to being influenced by marketing engagements. This not only has consequences for individual consumers but for society as a whole as well. It is imperative for marketers and advertisers to shift away from ultimately only selling their company's product. It should be an objective to help others. This extended examination unpacks the complex relationship between marketing, consumer suffering, and mental and physical well-being outcomes, particularly in regards to lifestyle ailments involving eating behaviors and eating disorders. This darker side of consumption exposes how marketing engagements can support a consumption addicted culture as advertised products allure consumers with excitement and clever advertising messaging encourages an even excessive consumption conflict. This dark side leads to immediate health consequences and here, even a larger issue is the negative implications to society as a whole, raising ethics questions regarding the company's responsibility for influencing public health..
Aligning with our nutritional needs and adhering to long-standing food intervals forms a bond with food that transcends taste and trends. Healthy food practices involve consuming food at appropriate intervals, resisting taste temptations, developing awareness of your body and minimizing food waste. Raising awareness of scientific eating practices involves educational interventions that spurs the concept of a full spectrum of nutrition and mindful eating. Educational interventions need to extend beyond traditional education and must include educational participatory/experiential activities, cooking classes/workshops and community opportunities. Utilizing digital methods to promote educational methods ensures greater accessibility, while wellness programs at work can assist in extending educational methods. A comprehensive and dynamic approach to education engages individuals in making informed and health-oriented decisions that creates a society which values wellness and sustains positive lifestyle activities for future generations.
Keywords: Health-Conscious, Society, Lifestyle, Generations, Education, Health Risks.
| 44 |
Author(s):
Dr. Padma Latha .
Page No : 1-7
|
AI-Driven Analysis of Patient Feedback for Quality Improvement in Healthcare Services
Abstract
Artificial Intelligence (AI) has emerged as a powerful tool for analyzing patient feedback to drive quality improvement in healthcare services. By leveraging advanced natural language processing and machine learning techniques, AI enables the efficient processing of large volumes of unstructured patient comments from diverse sources such as surveys, social media, and online reviews. This facilitates the extraction of meaningful insights related to patient satisfaction, common concerns, and areas needing improvement. AI-driven feedback analysis supports healthcare providers in making data-informed decisions, enhancing patient-centered care, and optimizing operational workflows. Despite challenges including data privacy, algorithmic bias, and integration into clinical settings, ongoing innovations in AI offer promising avenues for more transparent, equitable, and proactive healthcare quality management. This article reviews AI methodologies, practical applications, ethical considerations, and future trends in transforming patient feedback into actionable intelligence that can significantly improve healthcare delivery.
| 45 |
Author(s):
Supritha Bhandarkar.
Page No : 1-7
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AI-Driven Tools for Assessing and Managing Chronic Pain
Abstract
Chronic pain affects millions globally, presenting significant challenges due to its complex, multifactorial nature and reliance on subjective assessments. AI-driven tools offer a transformative approach by enabling objective, continuous, and personalized pain evaluation and management. Leveraging machine learning, natural language processing, wearable biosensors, and multimodal data integration, these technologies enhance pain assessment accuracy, facilitate early detection of exacerbations, and support tailored treatment plans. Despite promising benefits such as improved patient outcomes, reduced opioid dependency, and enhanced healthcare efficiency, challenges including data privacy, ethical considerations, algorithmic bias, and clinician-patient acceptance must be addressed. This article explores the current landscape of AI applications in chronic pain care, data sources and collection methods, implementation barriers, and ethical implications. It further discusses future research directions, emphasizing the potential of AI to shift chronic pain management from reactive symptom control to proactive, holistic, and patient-centered care.
| 46 |
Author(s):
Ashwin Naik.
Page No : 1-7
|
Developing AI Algorithms for Personalized Cancer Immunotherapy Plans
Abstract
Cancer immunotherapy has transformed oncology by enabling the immune system to target tumors, yet significant variability in patient responses underscores the urgent need for personalized treatment approaches. Artificial Intelligence (AI), through advanced machine learning and deep learning techniques, offers powerful tools to analyze complex, multi-dimensional patient data—including genomics, proteomics, imaging, and clinical records—to predict individual responses, optimize therapy selection, and monitor treatment outcomes dynamically. This article explores the development of AI algorithms tailored for personalized cancer immunotherapy planning, detailing the data integration processes, modeling strategies, and personalization frameworks that enable precise and adaptive treatment regimens. It also addresses challenges such as data heterogeneity, model interpretability, ethical considerations, and regulatory hurdles. By reviewing current clinical applications and envisioning future innovations, the article highlights AI’s transformative potential to enhance diagnostic accuracy, improve patient outcomes, and reduce adverse effects in cancer immunotherapy. Multidisciplinary collaboration and patient-centered design are essential to realize AI-driven precision oncology, ultimately advancing more effective and safer cancer care worldwide.
| 47 |
Author(s):
Abegail S. Dionisio, Joshua J. Frias, Joymie M. Gonzales, Brandon James P. Maningas, Xyrell Marc Andrei O. Siapno.
Page No : 1-7
|
The Interconnection of Societal Values on Student Identity Centrality and Friendship Ties
Abstract
This research explores how societal values connect to student identity centrality and friendship ties, which are the key factors in shaping students' educational and interpersonal development. However, prior research was limited to 173 Grade 7 students from a public school in Malolos, Bulacan, and was restricted from examining various kinds of societal values. By expanding the research framework, the study may provide valuable insights that inform educational policies and enhance student development strategies. The data in this research were gathered using a quantitative approach by giving the respondents structured questionnaires. The correlation analysis of societal values on student identity centrality and friendship ties revealed that societal values play a big role in molding the students' sense of identity and reinforce that cultural and social norms influence individual self-perception and behavior within an academic setting. In addition, the fundamental societal values become important elements for forming and deepening valuable friendships. The study findings demonstrate that students firmly support societal values that they display through their everyday actions in their environment.
Keywords: societal value, student identity centrality, friendship ties
| 48 |
Author(s):
Ratnaraj Kamble.
Page No : 1-7
|
Design and development of faulty product detection and separation system
Abstract
Ensuring product quality in manufacturing is critical for maintaining efficiency, reducing waste, and meeting regulatory standards. Traditional quality control methods, such as manual inspection, are prone to human error and inefficiency, especially in high-speed production environments. This research focuses on the development of an automated faulty product detection and separation system utilizing ultrasonic and infrared (IR) sensors. The system is designed to work on a conveyor belt, detecting faulty products based on two key parameters: height variations and sticker presence.
The ultrasonic sensor measures the height of products in real time, identifying any deviations beyond a predefined threshold. Simultaneously, the IR sensor detects the presence of stickers on bottles, ensuring that only properly labeled products proceed further. Faulty products—either due to incorrect height or missing stickers—are automatically separated from the production line using a mechanical sorting mechanism. This dual-sensor approach enhances quality control by providing accurate and reliable defect detection.
The system is designed to be cost-effective, scalable, and adaptable to various industries, including food and beverage, pharmaceuticals, and consumer goods manufacturing. Preliminary tests indicate a high detection accuracy and efficient rejection of defective products, reducing reliance on manual inspection while improving overall production speed.
This research contributes to advancing automated quality control systems by integrating real-time sensor-based inspection and sorting mechanisms. The findings demonstrate the potential of this system to improve manufacturing efficiency, reduce defects, and ensure consistent product quality, making it a viable solution for modern production environments.
Keywords: Automated Quality Control, Ultrasonic Sensor, Infrared Sensor, Conveyor Belt, Faulty Product Detection, Sorting Mechanism.
| 49 |
Author(s):
Navneet chauhan.
Page No : 1-7
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THE IMPACT OF INFLUENCER MARKETING ON CONSUMER BEHAVIOR IN THE GEN Z POPULATION
Abstract
Amidst the growing dominance of social media in shaping consumer culture, influencer
marketing has emerged as a powerful mechanism for influencing digitally native audiences.
This study critically examines how three key variables—social media usage, influencer
engagement, and purchase behavior—interact to shape the consumption decisions of
Generation Z consumers. Drawing on a cross-sectional, survey-based design, quantitative
data were collected from 150 Gen Z respondents aged 18–26 and analyzed using descriptive
statistics, Pearson’s correlation, and linear regression. Results reveal that while social media
usage exerts a moderate influence, influencer engagement—operationalized through trust,
credibility, and authenticity—more strongly predicts purchase behavior. Instagram emerged
as the most influential platform, with lifestyle-oriented content (e.g., fitness, fashion, and
travel) driving the highest engagement. These findings confirm the primacy of psychological
and relational factors in influencer effectiveness and underscore the need for marketers to
prioritize content resonance over mere platform visibility. The study advances digital
marketing scholarship by contextualizing Gen Z consumer behavior within an evolving
attention economy and offers actionable insights for brands seeking meaningful engagement
with this cohort.
| 50 |
Author(s):
Premi S.
Page No : 1-8
|
Talent Acquisition process with reference to Toppaz Industries
Abstract
This project report, titled “Talent Acquisition Process with Reference to Topaaz Industries,” examines the company’s strategic approach to acquiring top talent. Unlike traditional recruitment, talent acquisition is an ongoing, data-driven process involving workforce planning, employer branding, sourcing, assessment, and onboarding. The study highlights that while the process is generally effective, external market competition and internal practices impact its success. Statistical analyses show the importance of continuous improvement, inclusive hiring, and a candidate-focused strategy to enhance recruitment outcomes and support long-term organizational growth.
| 51 |
Author(s):
Dr. Manjunath Gowda.
Page No : 1-8
|
AI-Enhanced Monitoring Systems for Managing Chronic Respiratory Diseases
Abstract
Chronic respiratory diseases (CRDs) such as asthma and chronic obstructive pulmonary disease (COPD) pose substantial health challenges globally, requiring continuous monitoring for effective management. Traditional monitoring methods are often limited by episodic data collection and subjective assessments, which can delay intervention and worsen patient outcomes. Artificial intelligence (AI) offers transformative potential to overcome these limitations by integrating data from wearable sensors, environmental monitors, and electronic health records to enable real-time, personalized monitoring. AI algorithms can detect early signs of disease exacerbation, predict risk, and support tailored interventions, shifting care from reactive to proactive models. This article reviews current AI applications in CRD monitoring, explores the components of AI-enhanced systems, discusses clinical benefits, and addresses challenges such as data privacy, model bias, and integration barriers. We also highlight future innovations poised to advance precision respiratory medicine, improving patient quality of life while reducing healthcare costs. Through multidisciplinary collaboration and ethical implementation, AI-driven monitoring systems promise to revolutionize chronic respiratory disease management worldwide.
| 52 |
Author(s):
Dr. Shankar C. Patil.
Page No : 1-8
|
AI-Enhanced Screening Tools for Early Detection of Neurodegenerative Diseases
Abstract
Neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and ALS pose significant global health challenges due to their progressive nature and often late diagnosis. Early detection is crucial for effective intervention and improved patient outcomes, yet current screening methods face limitations in sensitivity, accessibility, and objectivity. Artificial intelligence (AI) offers transformative potential by analyzing complex multimodal data—including neuroimaging, genetic profiles, clinical records, and behavioral metrics—to identify subtle early signs of neurodegeneration. This article explores the fundamentals of AI in medical screening, advances in AI-enhanced imaging analysis, integration of multimodal datasets, and AI-powered cognitive and behavioral assessments. Real-world clinical applications and case studies illustrate the benefits and current challenges of AI deployment, including ethical, legal, and privacy considerations. Future innovations, such as federated learning, wearable biosensors, and explainable AI, promise to further enhance early detection and personalized screening. Responsible development and multidisciplinary collaboration are essential to maximize AI’s impact in proactive neurodegenerative disease management.
| 53 |
Author(s):
Selva Raj.
Page No : 1-8
|
Developing AI Models for Predicting Hospital Readmission Rates
Abstract
Artificial Intelligence (AI) has emerged as a transformative tool for predicting hospital readmission rates, a critical challenge in healthcare that impacts patient outcomes and costs. By leveraging machine learning algorithms and integrating diverse data sources—such as electronic health records, patient demographics, clinical histories, and social determinants—AI models can accurately identify patients at high risk for readmission. These models enable healthcare providers to implement targeted interventions, improving care quality and reducing avoidable hospitalizations. Despite challenges including data quality issues, model interpretability, integration barriers, and ethical considerations, ongoing advancements in AI techniques and collaborative efforts among clinicians, data scientists, and policymakers hold promise for more effective, equitable, and scalable predictive solutions. This article reviews the fundamentals of AI in healthcare, data preparation strategies, model development processes, real-world applications, and future directions for enhancing hospital readmission prediction, emphasizing the critical role of AI in transforming patient care and healthcare management.
| 54 |
Author(s):
Dhirendra Kumar.
Page No : 1-9
|
The Impact of Inventory Management on Business Profitability: Enhancing Automobile Logistics for a Seamless Customer Experience
Abstract
Inventory management plays a critical role in enhancing business profitability by ensuring that
companies maintain an optimal balance between supply and demand. Efficient inventory
practices help businesses reduce holding costs, minimize stockouts, and avoid overstocking, all
of which can lead to significant cost savings. Proper management also enables companies to
streamline their operations, improve customer satisfaction, and respond more effectively to
market trends and shifts in consumer behavior. The use of modern technologies, such as
inventory management systems (IMS) and data analytics, has further revolutionized the way
businesses track and manage their stock levels. These tools provide real-time data, allowing
businesses to forecast demand more accurately and make informed decisions on procurement,
storage, and distribution. On the other hand, poor inventory management can result in lost sales,
excess inventory, and a weakened cash flow, which directly impacts profitability. By adopting
best practices in inventory management, businesses can optimize their operational efficiency,
reduce waste, and create a competitive advantage in the marketplace, ultimately leading to
improved profitability. This paper explores the influence of inventory management on
profitability, analyzing various strategies and tools that businesses can employ to enhance their
inventory systems and drive sustainable financial growth.
| 55 |
Author(s):
Asif Iqbal Hajamydeen, Muhammad Abas Suhaimy, Muhammad Irsyad Abdullah.
Page No : 1-9
|
Advanced Deep Learning Techniques for Comprehensive Detection of Eye Disease Using Retinal and OCT Imaging
Abstract
Early detection of eye diseases are crucial for preventing vision loss and ensuring timely treatment. This paper explores the application of advanced deep learning techniques for the comprehensive detection of various eye diseases using retinal and Optical Coherence Tomography (OCT) imaging. The detection of eye diseases, particularly myopia, is an important healthcare challenge in Malaysia due to the increasing prevalence of vision-related disorders. This research focuses on developing an AI-driven solution to address this challenge, with the primary focus on detecting myopia. However, the system is also capable of identifying other conditions such as acrima, retinal diseases, origa, diabetic retinopathy, cataract, glaucoma and age-related macular degeneration. The study utilizes Convolutional Neural Networks, achieving a high accuracy of 97.87% for myopia detection. Fine-tuning was applied to a pre-trained CNN model, leveraging transfer learning to enhance the model's performance. By employing advanced deep learning architectures, this research enhances diagnostic accuracy and efficiency, providing a robust framework for the detection of a wide range of ocular diseases. The results highlight the potential of CNNs in revolutionizing eye care, emphasizing the role of AI in improving diagnostic capabilities and its integration with retinal and OCT imaging to ensure timely diagnosis and treatment.
| 56 |
Author(s):
Nikhil Tiwari.
Page No : 1-9
|
Impact of Inflation on Investment Decision in India.
Abstract
Inflation — the general rise in prices — is a critical macroeconomic factor affecting investment returns and decisions. In India, consumer price inflation has recently moderated to around the RBI’s 4% target (averaging ≈4–5% in 2024)data.worldbank.orgfocus-economics.com, but historical volatility has been high (e.g. October 2024 CPI 6.2%, highest since Aug’23livemint.com). Inflation erodes real returns: for example, over the past decade India’s average inflation was ~5.2%, turning a 12% nominal equity return into only ~6.8% real, and a 7% fixed deposit return into just ~1.8% realeconomictimes.indiatimes.com.
However, empirical analyses show that inflation by itself has only a weak direct effect on equity pricesijrpr.comijrpr.com; instead, stock markets are more sensitive to interest rates, monetary policy, and investor sentiment. Moderate inflation (2–4%) often coincides with robust market performanceresearchgate.netijrpr.com, whereas high inflation spikes have historically triggered market corrections and shifts to safe assets (“flight to safety” into gold and bonds)ijrpr.com. This report reviews recent Indian data and research, using CPI trends (RBI/MoSPI), equity and bond returns, and investor surveys to analyze inflation’s impact.
We apply both quantitative (correlation/regression) and qualitative (sentiment analysis, case studies) methods. Key findings include: (a) portfolio strategies should emphasize inflation hedging (e.g. inflation-indexed bonds, real assets) and sector rotation (favoring essentials and dividend-paying stocks)researchgate.neteconomictimes.indiatimes.com; (b) fundamental analysis (which explicitly accounts for inflation and interest ratesinvestopedia.cominvestopedia.com) and technical analysis (monitoring market trends and sentiment) can both inform timing decisions; (c) investors must focus on real (inflation-adjusted) returns, and policymakers should strengthen inflation-targeting frameworks and expand inflation-linked instrumentseconomictimes.indiatimes.comeconomictimes.indiatimes.com. The report concludes with tailored recommendations for individual investors, financial educators, and policymakers, aiming to preserve purchasing power and improve investment outcomes in India’s evolving economic environment.
| 57 |
Author(s):
Dr.Sindhura Kannappan, Abdullah Masood.
Page No : 1-9
|
Succeeding in Business and Finance: Enhancing Strategic Decision-Making, Innovation, and Operational Efficiency in the Leather Industry
Abstract
This article investigated the critical factors influencing business and financial success in the leather industry, specifically focusing on the interplay of strategic decision-making, innovation, and operational efficiency. The study aims to analyze the environmental impact of conventional leather production, explore strategies for economic resilience, and understand consumer preferences to enhance customer satisfaction within this sector. A quantitative case study approach was employed, focusing on Leather Export industry in TamilNadu. Data was collected from 152 employees and operational units via structured questionnaires. Statistical analyses included multiple regression. Descriptive statistics revealed high agreement among respondents across all variables with low variability. The regression model significantly predicted Operational Efficiency, with Technology Integration and Supply Chain Optimization identified as statistically significant positive predictors. The study concludes that strategic interventions, particularly in adopting sustainable and eco-friendly alternatives and addressing ethical concerns, coupled with continuous innovation and improvements in operational efficiency, are paramount for the leather industry's long-term business and financial sustainability.
| 58 |
Author(s):
Dr.Sindhura Kannappan, Lavanya M K.
Page No : 1-9
|
Gamified Training in Food Safety: Enhancing Compliance and Workplace Engagement in the Indian Food Industry
Abstract
This research investigated the efficacy of gamified training in improving food safety compliance, employee engagement, and knowledge retention within India's diverse food industry. Traditional training methods often struggle with low engagement and inconsistent application, necessitating innovative approaches. Employing a descriptive research design with a sample of 104 food industry professionals in India, the study utilized a structured questionnaire and statistical analyses including demographic profile of respondents and regression. Crucially, gamification elements emerged as the sole statistically significant predictor of food safety compliance, explaining 28.7% of its variance. This indicates that core game mechanics are highly effective in driving adherence to safety protocols. The study also found no significant impact of gender or educational background on training outcomes, suggesting broad applicability. This report underscores the transformative potential of gamified training as a scalable and inclusive solution to foster a robust culture of food safety in India.
| 59 |
Author(s):
Sonal Kumar Singh.
Page No : 1-10
|
Optimization on First Mile, Mid Mile & Last Mile in Oscm
Abstract
Delhivery Ltd., a prominent player in India's logistics and supply chain industry, has emerged as a trailblazer in revolutionizing the way goods are transported and delivered across the nation. With its robust network, state-of-the- art technology, and relentless pursuit of efficiency, Delhivery has made a significant mark in optimizing three critical stages of logistics operations: First Mile, Mid Mile, and Last Mile. These operations serve as the foundation of the company's logistics ecosystem, ensuring the smooth and seamless movement of goods from origin to destination.
First Mile Operations form the initial link in the logistics chain, where goods are collected from suppliers, manufacturers, or retailers and transported to distribution centers or warehouses. This stage is vital because it sets the tone for the entire logistics journey. Efficient First Mile operations require meticulous planning, accurate scheduling, and effective coordination to prevent delays and maintain the quality of goods. Delhivery achieves this through advanced technology solutions such as real-time tracking systems, data analytics, and automated processes. By leveraging predictive analytics, the company forecasts demand and optimizes its pickup schedules, ensuring timely collection and a streamlined transition to the next phase.
At the heart of Delhivery's innovation is its commitment to reducing inefficiencies and enhancing operational transparency. First Mile operations often face challenges such as variability in supplier locations, fluctuating volumes, and differing transportation modes. To address these complexities, Delhivery employs tailored logistics strategies that take into account the unique requirements of each client. By integrating technology with a customer- centric approach, the company ensures that First Mile operations are not only efficient but also adaptable to the diverse needs of its clients.
Mid Mile Operations represent the intermediary stage in the logistics process, where goods are transported from distribution centers to regional hubs or sorting facilities. This phase is essential for consolidating shipments,
optimizing routes, and minimizing transit times. Mid Mile operations serve as the backbone of the logistics chain, linking the origin with the destination through efficient connectivity. Delhivery's extensive transportation network, combined with its advanced optimization algorithms, plays a pivotal role in enhancing the efficiency of Mid Mile operations.
One of the key challenges in Mid Mile logistics is managing transportation assets effectively to balance cost, speed, and reliability. Delhivery addresses this challenge by employing dynamic routing technologies and fleet management systems that allow real-time adjustments based on traffic conditions, weather, and other variables.
These systems not only improve transit times but also reduce fuel consumption, aligning with the company's commitment to sustainability.
In addition, Delhivery's sorting facilities are equipped with cutting-edge automation technologies that enable high- speed processing and accurate segregation of goods. This ensures that shipments are efficiently handled and dispatched to the appropriate Last Mile hubs, reducing errors and enhancing overall operational efficiency. The company's ability to scale its Mid Mile operations while maintaining a high level of precision is a testament to its logistical expertise. Delhivery Ltd stands as a prominent player in India's logistics and supply chain sector, with a specialization in e-commerce and enterprise solutions. The company operates through a vast network, incorporating cutting-edge, technology-enabled strategies to streamline transportation, warehousing, and order processing.
Its operations commence with first-mile pickup, where consignments are gathered from sellers and subsequently sorted at state-of-the-art automated hubs. These packages are then routed via meticulously planned pathways that combine surface and air transportation networks. Delhivery utilizes sophisticated tracking systems and data-driven analytics to provide real-time shipment updates and ensure prompt last-mile delivery.
In the realm of supply chain management, Delhivery offers comprehensive solutions such as inventory control, predictive analytics for demand, and handling returns efficiently. Harnessing the power of artificial intelligence and automation, the company achieves operational optimization, minimizes delivery times, and reduces costs. Its adaptable logistics framework caters to diverse industries, from online marketplaces to traditional retail setups, delivering both reliability and scalability.
Last Mile Operations constitute the final and most customer-facing stage of the logistics process, where goods are delivered from regional hubs to the end customer. This stage is often considered the most challenging due to its complexity and direct impact on customer satisfaction. Last Mile operations demand a delicate balance between speed, accuracy, and cost-effectiveness to meet the growing expectations of customers in a fast-paced market.
Delhivery's Last Mile optimization strategies are driven by technology-enabled solutions such as route optimization tools, real-time delivery tracking, and crowdsourced delivery models. Route optimization tools help the company plan efficient delivery routes, minimizing travel distances and enhancing productivity. Real-time tracking systems provide customers with visibility into their deliveries, fostering transparency and trust. Crowdsourced delivery
models leverage a network of local delivery agents to expand coverage and ensure timely deliveries, particularly in remote areas.
The challenges of Last Mile operations, such as traffic congestion, delivery time windows, and varied delivery preferences, require innovative solutions. Delhivery addresses these challenges through flexible delivery options, including same-day and scheduled deliveries, to cater to the diverse needs of its customers. The company's investment in technology and infrastructure ensures that Last Mile operations are not only effective but also scalable, accommodating the growing demand for reliable logistics services.
Delhivery Ltd.'s approach to optimizing First Mile, Mid Mile, and Last Mile operations exemplifies its commitment to redefining logistics standards in India. By integrating advanced technologies, data-driven insights, and customer- centric strategies, the company has established itself as a leader in the logistics industry. Its ability to address the unique challenges of each stage of the logistics process highlights its innovative spirit and operational excellence. Through continuous improvement and a focus on efficiency, Delhivery continues to set benchmarks in logistics optimization, paving the way for a more connected and streamlined supply chain ecosystem. This introduction provides a comprehensive overview of the strategies and innovations employed by Delhivery in transforming logistics operations, offering a glimpse into its impact on the industry and the broader economy.
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Author(s):
Shyamkumar Parikh.
Page No : 1-10
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Green Energy Innovations: Alternatives to Fossil Fuels
Abstract
The global energy landscape is undergoing a significant transformation as conventional fossil fuel-based power generation becomes increasingly unsustainable due to environmental degradation, rising fuel costs, and finite resource availability. To address these challenges and meet the growing energy demand, it is crucial to explore innovative, clean, and resilient alternatives. This paper investigates a range of future-oriented energy technologies that promise to revolutionize power generation.
Key focus areas include nuclear fusion, which offers the potential for nearly limitless and clean energy; space-based solar power, which can capture uninterrupted solar energy beyond Earth's atmosphere; and hydrogen fuel cells, known for their efficiency and zero-emission profile. The study also examines microbial fuel cells that convert organic waste into electricity, ocean thermal energy conversion (OTEC) that utilizes temperature gradients in ocean water, and the integration of artificial intelligence in smart grids to enhance energy efficiency, storage, and distribution.
Together, these emerging technologies provide scalable, eco-friendly, and decentralized solutions that could play a critical role in addressing the energy crisis while supporting climate goals. This paper aims to offer a comprehensive perspective on how these next-generation systems can be adopted to build a more sustainable and secure energy future.
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Author(s):
Nancy Rohilla.
Page No : 1-11
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HISTORY AND EVOLUTION OF POLICE SYSTEM IN INDIA
Abstract
The evolution of the police system in India traces a profound transformation from informal communitybased models of security in ancient times to a centralized bureaucratic structure under British rule and the continued legacy of that model in independent India. Ancient Indian scriptures and epics like Manusmriti and Arthashastra reveal that structured policing and crime categorization existed as early as the Vedic and Mauryan periods. Medieval India saw a fusion of military and administrative functions in policing, especially during the Mughal and Maratha regimes. However, modern institutionalization began during the British era with the Police Act of 1861, which created a centralized, hierarchical, and often repressive force. Although several commissions and reforms have followed since independence, the colonial ethos and structure largely remain intact. This historical overview underscores the need for comprehensive police reform aligned with democratic ideals and public accountability in India.
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Author(s):
Amrita Rastogi.
Page No : 1-11
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WIRELESS SECURITY IN IoT : A NOVEL APPROACH FOR PREVENTING MAN-IN-THE MIDDLE ATTACKS
Abstract
The Internet of Things (IoT) has rapidly transformed several industries, including transportation, smart homes, healthcare, and industrial automation. However, with the increasing reliance on the inter-relatedness of IoT devices, we face significant security threats, such as Man-in-the-Middle (MitM) attacks and Distributed Denial-of-Service (DDoS) attacks. MitM attacks allow attackers to listen to and manipulate communication between the device, leading to data exposure and unauthorized access, while DDoS attacks consume network resources, reducing device life expectancy and increasing energy usage. This research proposes a security framework to mitigate MitM and DDoS attacks in IoT and wireless sensor networks (WSNs). This framework utilizes strong encryption solutions, mutual authentication protocols, and blockchain-based trust management to support security while lowering computational overhead. The proposed framework prevents unauthorized access through lightweight ciphering approaches appropriate for resource-limited IoT devices, while blockchain technology utilizes a decentralized, tamper-proof ledger for device authentication based on communication logs. Proposed research identifies and discusses important security and privacy challenges: linkability, unauthorized communication, and side-channel attacks.
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Author(s):
Utkarsh Barman,Sumit Koul(Associate Professor),School of Business.
Page No : 1-11
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ROLE OF AI IN RECRUITMENT & TALENT ACQUISITION
Abstract
Artificial Intelligence (AI) has significantly reshaped the landscape of recruitment and talent acquisition. Traditional hiring methods, which relied heavily on manual efforts and subjective judgments, often faced inefficiencies, bias, and delays. In contrast, AI-powered tools—such as Applicant Tracking Systems (ATS), intelligent chatbots, predictive analytics, and automated video assessments—are revolutionizing how companies identify and engage talent.
This report explores the role of AI in enhancing hiring outcomes by improving speed, reducing human error, and fostering fairer recruitment practices. It also critically examines challenges, including ethical dilemmas, data security concerns, and the risk of algorithmic bias. Real-world examples like Unilever’s success and Amazon’s setbacks with AI-driven recruitment provide insight into the diverse impact of these technologies.
With credible industry data from sources such as LinkedIn, Gartner, and PwC, this study outlines how AI is set to redefine recruitment by drastically shortening hiring cycles and improving candidate experience. However, the report also emphasizes the need for responsible AI use, highlighting the importance of human oversight to maintain fairness, transparency, and integrity in talent acquisition.
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Author(s):
Swarnalata Sahoo.
Page No : 1-11
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CRITICAL PEDAGOGY EMPOWERS STUDENTS THROUGH TRANSFORMATIVE EDUCATION
Abstract
Critical pedagogy is an educational approach rooted in the belief that education should be a means of challenging oppression and fostering critical consciousness. Drawing from the works of Paulo Freire and other critical theorists, this research explores how critical pedagogy empowers students by enabling them to question societal structures, recognize systemic injustices, and become agents of transformation. Using secondary research methods, this paper analyzes existing literature and case studies from diverse educational contexts to understand the mechanisms through which critical pedagogy cultivates transformative learning experiences. The study poses the central research question: How does critical pedagogy empower students through transformative education? The significance of this inquiry lies in the growing global need for education that not only imparts knowledge but also promotes equity, justice, and democratic participation. The research employs a qualitative interpretative approach, synthesizing scholarly articles, empirical studies, and theoretical texts that engage with critical pedagogy. Findings reveal that critical pedagogy enhances student agency, fosters dialogue, encourages reflective thinking, and bridges the gap between academic learning and real-world struggles. The discussion emphasizes the role of educators as co-learners and facilitators of change, and the necessity of integrating critical pedagogy into curricula at all levels. In conclusion, the paper advocates for the broader adoption of critical pedagogy to transform education into a liberatory practice that empowers learners, challenges the status quo, and contributes to building a more just and inclusive society.
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Author(s):
Abhishek Tiwari.
Page No : 1-11
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The Role of Distribution Centers in Transforming Last-Mile Delivery for Indian E-commerce””
Abstract
In the dynamic landscape of Indian e-commerce, last-mile delivery stands as a crucial yet complex segment of the supply chain, particularly across rural and semi-urban regions. This study investigates the transformative impact of strategically positioned and technologically advanced distribution centers (DCs) on enhancing last-mile delivery efficiency, reliability, and customer satisfaction. Using a mixed-methods research design, the study draws insights from logistics professionals, delivery personnel, and end-consumers across varied geographic contexts.
Findings reveal that DCs located closer to consumer clusters significantly reduce transit times and operational costs. Furthermore, the integration of technologies—such as real-time tracking, route optimization, and multilingual delivery applications—enhances delivery precision and improves communication across diverse user bases. The study also highlights the value of employing local workforces and developing climate-resilient infrastructure to address regional and seasonal delivery challenges.
Based on empirical data, the study recommends strategic distribution center placement, investment in automation, localized recruitment, and partnerships with third-party logistics (3PL) providers to build scalable and cost-effective delivery networks. Ultimately, this research positions distribution centers as key enablers of inclusive and sustainable growth in India's e-commerce sector, particularly in underserved markets where traditional logistics frameworks are inadequate.
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Author(s):
Vianna Grace L. Agacer, Czyrus John V. Bautista, Chizenn Mae V. Bañez, Kris Anne Mae R. Dela Cruz, Angelica P. Haciñas.
Page No : 1-12
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Shaping Student’s Values: The Influence of Implementing Value-Based Education on Emotional Intelligence
Abstract
The main goal of this study was to explore the influence of implementing value-based education (VBE) on the emotional intelligence of high school students in Public School in Bulakan in the Division of Bulacan. The study emphasized the importance of holistic development in education, focusing on the integration of core values such as Maka-Diyos (to God), Maka-Tao (to People), Maka-Kalikasan (to Nature), and Maka-Bansa (to Country) within the curriculum. Through a quantitative research method, the study employed a survey questionnaire to assess students' reflections on their values before and after the implementation of the VBE lesson plans. The findings revealed a significant positive impact of VBE on students' EI, highlighting improvements in their understanding and application of core values. The results showed that the students exhibited enhanced emotional awareness, emotional management, social-emotional awareness, and relationship management skills. The study concluded that value-based education plays a crucial role in shaping students' values, fostering their emotional intelligence, and preparing them to become responsible and compassionate citizens. Recommendations for further research and the integration of VBE into educational practices are also discussed.
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Author(s):
Harsh Singh.
Page No : 1-13
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Impact Of E-Commerce On Traditional Supply Chain Models
Abstract
This thesis investigates the transformative impact of e-commerce on traditional supply chain models, exploring how digital platforms have reshaped logistics, distribution, and customer service. The rise of e-commerce has challenged the efficiency-focused, linear structure of conventional supply chains, driving a shift towards agile, technology-driven, and customer-centric systems. Through a mixed-method research approach—comprising surveys, interviews, and case studies—this study analyzes operational changes across various sectors, with a focus on emerging technologies such as AI, IoT, and blockchain. Findings reveal that e-commerce enhances supply chain visibility, reduces lead times, and promotes direct-to-consumer (DTC) models, while also introducing new challenges in reverse logistics, sustainability, and technological adaptation. The research underscores the strategic importance of integrating digital tools, restructuring logistics networks, and upskilling supply chain talent to remain competitive in an evolving digital economy. This study offers practical recommendations for businesses seeking to modernize their supply chains and provides a framework for future research on digital transformation in logistics.
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Author(s):
PRIYANSHU RAI.
Page No : 1-13
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Impact of dabur’s rural marketing strategies on consumer buying behaviour
Abstract
India's rural population, comprising over 65% of the total demographic, plays a crucial role in the nation’s consumption patterns. With increasing purchasing power, better infrastructure, and rising awareness, rural markets have become a significant area of interest for fast-moving consumer goods (FMCG) companies. Among the prominent players in this domain, Dabur India Ltd., a heritage-rich and trust-driven brand, has effectively leveraged rural marketing strategies to reach the grassroots of India. This study explores and evaluates the impact of Dabur’s rural marketing strategies on consumer buying behaviour in rural India, with particular focus on awareness, attitudes, buying frequency, and brand loyalty.
The core objective of this research is to investigate how rural-specific marketing initiatives undertaken by Dabur influence the decision-making process of rural consumers. The study delves into the strategic approaches Dabur has adopted, such as product adaptation, localized promotions, pricing mechanisms, and distribution networks, tailored to the needs and limitations of rural consumers. In addition, the study assesses the extent to which these strategies have helped Dabur improve its market penetration, brand equity, and revenue in rural segments.
Dabur, being a brand rooted in Ayurveda and natural health care, has long-standing credibility among both urban and rural consumers. However, tapping into the diverse and often unpredictable rural markets required customized approaches. The study highlights several such tactics, including:
• Product Customization: Dabur has effectively tailored its products in terms of packaging size and pricing to suit the affordability and usage patterns of rural consumers. For instance, single-use sachets of Dabur Chyawanprash and smaller packs of Dabur Red Toothpaste have helped drive trials and repeat usage.
• Affordability and Value Proposition: Competitive pricing strategies were employed to match rural price sensitivity, without compromising on perceived value. Products were positioned to emphasize benefits most relevant to rural buyers—health, longevity, and trust.
• Distribution Networks: Dabur developed an extensive rural distribution network, including van campaigns and partnerships with local kirana stores, which enabled deep market penetration. The “Project Double” initiative expanded retail outreach by engaging rural sub-stockists and increasing the availability of products in remote villages.
• Rural Communication and Branding: Understanding the limited reach of mass media in rural areas, Dabur used localized, vernacular campaigns and engaged directly with the community through health camps, mobile vans, street plays, and rural fairs. These initiatives helped establish trust, spread awareness, and educate rural audiences about product benefits.
• Use of Influencers: Dabur’s strategy involved the use of local influencers, such as village elders, school teachers, and health workers, to build credibility. Word-of-mouth marketing played a vital role, especially for products in the healthcare and personal care segments.
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Author(s):
Santosh kumar.
Page No : 1-14
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IMPACT OF PATANJALI PRODUCTS ON RURAL MARKETING STRATEGIES AND CONSUMER BEHAVIOUR IN INDIAN VILLAGE
Abstract
This study investigates how Patanjali Ayurved Ltd. affects rural marketing tactics and village consumer behaviour in India. By emphasizing natural, affordable, and Ayurvedic items, Patanjali has greatly expanded into rural markets, changing conventional marketing strategies and consumer attitudes. In rural India, the study evaluates the efficacy of Patanjali's pricing, distribution, product modification, and marketing tactics. The study assesses the change in customer preferences, brand loyalty, and purchasing behaviour using both quantitative and qualitative approaches, such as surveys, interviews, and observational techniques. The results indicate that Patanjali has had a significant impact on rural consumption patterns and raising awareness of indigenous items.
________________________________________
Agencies use marketing as a tool to communicate with customers and educate them about the various uses of their products and services. It's a crucial component of drawing in the target market for a chosen product, and businesses employ a variety of cutting-edge or tried-and-true strategies to stay ahead of the competition and establish their place in the market.
The process often begins immaturely with an assessment of the internal and external commercial company environment, which comprises knowledge and strategy limitations including financial, cultural, political, legal, and technological elements.
.
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Author(s):
Cristine Joy Marquez, Marie Nicole Evasco, Elaine Manag, Reden Alvario, Dorethy Samson.
Page No : 1-15
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The Development of Digital Storytelling in Values Formation for Secondary Students
Abstract
The main objective of this study is to develop digital storytelling in values formation for secondary students, particularly Grade 10 students. The general problem of this study was how digital storytelling to be developed for the value formation of secondary students. The study utilized quantitative descriptive developmental research. The students and teachers are respondents. Developed digital storytelling was evaluated by 1 Information Technology teacher and 2 Technology Teaching and Learning Teachers to assess the content quality, technical quality, instructional quality and other findings. The study adopted the LRMDS for the evaluation of the digital storytelling, Technology Acceptance Model was used to know the level of acceptability of digital storytelling and System Usability Scale to know the level of the usability of digital storytelling. To know the level acceptability of digital storytelling, general mean was computed and for the system usability scale percentile rank was used. The findings show that there is a significant difference between the perception of the teachers and student in the level acceptability and usability of digital storytelling. The findings illustrate that teachers and students appreciate the development of digital storytelling. It is recommended for future researchers to study the effectiveness of digital storytelling in values formation for secondary students and to train the Values education teachers in the use of digital storytelling.
Keywords: digital story, development, values formation, acceptability, usability
| 71 |
Author(s):
Abhiratan pal.
Page No : 1-15
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THE INFLUENCE OF PATANJALI PRODUCTS IN INDIAN VILLAGE CONSUMER BEHAVIOR AND ANALYSIS OF RURAL MARKETING TACTICS.
Abstract
This thesis explores how Patanjali products have influenced rural marketing strategies and changed consumer behavior in Indian villages. Patanjali, known for its Ayurvedic and Swadeshi image, has grown rapidly in the FMCG sector and become a household name—especially in rural India. The brand’s focus on natural ingredients, affordable pricing, and a strong cultural connection has played a big role in its success among rural consumers.
The research looks at how Patanjali has changed the way companies approach rural markets. Traditional rural marketing focused mainly on low prices and limited options. But Patanjali brought in a new approach by offering products that are not only affordable but also seen as healthy and rooted in Indian traditions. Their marketing strategies, such as using Baba Ramdev’s image and promoting Indian values, have helped build trust among rural consumers.
Through surveys and interviews in different villages, this study found that people are increasingly choosing Patanjali products over other brands. Many villagers said they trust the brand because of its natural ingredients and because it feels “local” and not foreign. The wide range of products—from toothpaste to ghee—has also helped Patanjali become a one-stop choice for many rural families.
The thesis also highlights how other companies are now changing their own rural marketing strategies to keep up with Patanjali. They are rethinking their pricing, packaging, and messaging to better connect with rural consumers.
In short, Patanjali has done more than just sell products—it has changed how brands engage with rural India. This study shows how a brand that understands the values and needs of village consumers can reshape the entire rural market.
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Author(s):
Harsh Rai.
Page No : 1-16
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Consumer Behaviour and Decision-Making Patterns in the Used Indian Automobiles Industry in India
Abstract
The used Automobile industry in India has undergone a remarkable transformation over the past
decade, driven by evolving consumer preferences, increasing urbanization, and the rapid integration
of digital technologies. Traditionally dominated by unorganized players—local dealers, individual
sellers, and informal networks—this sector often lacked transparency, standardization, and customer
confidence. However, the emergence of digital platforms such as CARS24, Spinny, and CarDekho
has revolutionized the landscape, offering consumers a more organized, convenient, and trustworthy
way to buy and sell pre-owned vehicles.
Among these, Indian automobile industry has emerged as a frontrunner by leveraging data-driven
solutions and technology-enabled services. It provides features such as instant car valuation, online
listings, vehicle inspection at the doorstep, seamless documentation, and digital transactions. These
innovations have addressed many of the inefficiencies associated with the traditional used car market,
such as restricted market access, unclear pricing, and time-consuming negotiations.
Despite these advancements, consumer behavior in the digital used car segment remains influenced
by a variety of psychological and functional factors. Elements such as trust in digital platforms,
perceived risks (related to payments, authenticity, and quality), and expectations around service and
after-sales support continue to shape consumer decisions. Many first-time users, especially in semi
urban and rural areas, remain cautious due to concerns about fraud, hidden charges, and limited
awareness of digital processes.
This study aims to analyze the consumer decision-making process in India’s used car market, with a
special focus on digital platforms like CARS24, Car Dekho, Spinny, etc. It will examine key
influencing factors such as price sensitivity, trust, risk perception, platform usability, and service
quality. The research is based on secondary data from industry reports, market research studies, and
academic sources to identify the emerging patterns of consumer behavior in this domain. The insights
generated from this study will help digital automotive platforms like CARS24, Spinny, Car Dekho,
etc., enhance customer experience and build stronger engagement strategies.
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Author(s):
Dr. Biswajit Satpathy.
Page No : 1-16
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A TISM MODEL WITH THE TRIPLE BOTTOM LINE (TBL) AS THE ULTIMATE OBJECTIVE FROM THE BHAGAVAD GITA
Abstract
This work aspires to combine classical philosophical views with contemporary sustainability frameworks by formulating a Total Interpretive Structural Modelling (TISM) model that associates the eighteen chapters of the Bhagavad Gita with the Triple Bottom Line (TBL) paradigm, which encompasses social, environmental, and economic realms. Utilizing a qualitative-exploratory methodology, each chapter of the Gita is conceptualized as a variable within this analytical framework, thereby elucidating interconnections that collectively contribute to sustainable practices. The analysis employs Interpretive Structural Modelling (ISM) and MICMAC methodologies to delineate the hierarchical relationships, revealing foundational, integrative, and dependent chapters that collectively constitute a progressive ethical evolution. The findings indicate that the philosophical and ethical insights of the Gita—most notably those concerning self-awareness, duty, and detachment—provide a pragmatic, values-oriented framework for sustainable leadership and organizational strategies. By synthesizing spiritual insights with modern sustainability paradigms, this research advocates for a trans-disciplinary approach to enhancing organizational resilience and ethical governance, thereby positioning the Bhagavad Gita as an enduring guide for addressing contemporary challenges.
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Author(s):
Sanjeev Kumar.
Page No : 1-23
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“Consumer Perceptions of Digital Applications in India: A mixed Methods Exploration of Awareness, Trust and Usage Patterns”
Abstract
This research examines consumer perceptions towards digital credit applications in India,
focusing on Buy Now Pay Later (BNPL) services, payday loans, and instant credit cards. Using
a mixed-methods approach combining quantitative surveys (n=200) and qualitative case
studies (n=8), the study investigates awareness levels, usage patterns, perceived benefits and
risks, and trust factors across demographic segments. Findings reveal high adoption rates in
urban India, with varying levels of financial literacy influencing usage behaviors. While digital
credit has enhanced financial inclusion, concerns regarding debt accumulation, hidden charges,
and inadequate disclosures present significant challenges. The research contributes to
understanding fintech adoption in emerging markets and provides actionable recommendations
for creating a balanced digital credit ecosystem that promotes innovation while ensuring
consumer protection. This study is particularly relevant for the Indian context, where rapid
digitalization intersects with varying levels of financial literacy and significant socioeconomic
diversity.